Marek Kovář

3.5k total citations · 1 hit paper
64 papers, 2.7k citations indexed

About

Marek Kovář is a scholar working on Immunology, Oncology and Biomaterials. According to data from OpenAlex, Marek Kovář has authored 64 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Immunology, 22 papers in Oncology and 20 papers in Biomaterials. Recurrent topics in Marek Kovář's work include Nanoparticle-Based Drug Delivery (20 papers), Immune Cell Function and Interaction (19 papers) and Immunotherapy and Immune Responses (14 papers). Marek Kovář is often cited by papers focused on Nanoparticle-Based Drug Delivery (20 papers), Immune Cell Function and Interaction (19 papers) and Immunotherapy and Immune Responses (14 papers). Marek Kovář collaborates with scholars based in Czechia, United States and Belarus. Marek Kovář's co-authors include Jonathan Sprent, Onur Boyman, Charles D. Surh, Mark P. Rubinstein, Blanka Řı́hová, Jakub Tomala, Karel Ulbrich, Tomáš Etrych, J. Strohalm and Jared F. Purton and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Marek Kovář

60 papers receiving 2.7k citations

Hit Papers

Selective Stimulation of T Cell Subsets with Antibody-Cyt... 2006 2026 2012 2019 2006 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marek Kovář Czechia 27 1.5k 745 590 569 377 64 2.7k
Conlin P. O’Neil Switzerland 20 1.4k 0.9× 320 0.4× 1.2k 2.0× 568 1.0× 616 1.6× 27 2.9k
Matthias Bros Germany 28 1.2k 0.8× 479 0.6× 1.3k 2.3× 467 0.8× 276 0.7× 116 3.0k
Wilson S. Meng United States 24 822 0.5× 401 0.5× 844 1.4× 334 0.6× 246 0.7× 61 1.8k
Huijuan Song China 30 917 0.6× 555 0.7× 1.3k 2.1× 927 1.6× 1.1k 3.0× 88 3.0k
Shaomin Tian United States 27 957 0.6× 519 0.7× 1.1k 1.8× 702 1.2× 1.1k 2.9× 55 2.8k
Leslie R. Coney United States 18 1.1k 0.7× 391 0.5× 1.3k 2.2× 428 0.8× 275 0.7× 28 3.0k
Yohei Mukai Japan 32 807 0.5× 416 0.6× 1.6k 2.7× 398 0.7× 352 0.9× 102 3.0k
Gaëlle Vandermeulen Belgium 26 673 0.4× 300 0.4× 1.3k 2.2× 695 1.2× 475 1.3× 48 2.8k
Tomáš Mrkvan Czechia 22 548 0.4× 248 0.3× 318 0.5× 531 0.9× 288 0.8× 32 1.7k
Wenxue Ma United States 26 722 0.5× 624 0.8× 1.1k 1.9× 453 0.8× 352 0.9× 84 2.5k

Countries citing papers authored by Marek Kovář

Since Specialization
Citations

This map shows the geographic impact of Marek Kovář's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marek Kovář with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marek Kovář more than expected).

Fields of papers citing papers by Marek Kovář

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marek Kovář. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marek Kovář. The network helps show where Marek Kovář may publish in the future.

Co-authorship network of co-authors of Marek Kovář

This figure shows the co-authorship network connecting the top 25 collaborators of Marek Kovář. A scholar is included among the top collaborators of Marek Kovář based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marek Kovář. Marek Kovář is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Šírová, Milada, et al.. (2025). Temporal optimization of CD25-biased IL-2 agonists and immune checkpoint blockade leads to synergistic anticancer activity despite robust regulatory T cell expansion. Journal for ImmunoTherapy of Cancer. 13(8). e010465–e010465. 1 indexed citations
2.
Konefał, Rafał, Robert Pola, Volodymyr Lobaz, et al.. (2024). Dual Thermo- and pH-Responsive Polymer Nanoparticle Assemblies for Potential Stimuli-Controlled Drug Delivery. ACS Applied Bio Materials. 8(1). 271–284. 5 indexed citations
3.
Harazim, Hana, et al.. (2024). Year 2024 in review - Paediatric Anaesthesia and intensive care. 35(5). 311–313.
4.
Truxová, Iva, Jana Raková, Cyril Šálek, et al.. (2023). Type I interferon signaling in malignant blasts contributes to treatment efficacy in AML patients. Cell Death and Disease. 14(3). 209–209. 15 indexed citations
5.
Tsyklauri, Oksana, Veronika Niederlová, Juraj Michálik, et al.. (2023). Regulatory T cells suppress the formation of potent KLRK1 and IL-7R expressing effector CD8 T cells by limiting IL-2. eLife. 12. 15 indexed citations
6.
Kovář, Marek, Vladimír Šubr, Martin Studenovský, et al.. (2023). Chemosensitization of tumors via simultaneous delivery of STAT3 inhibitor and doxorubicin through HPMA copolymer-based nanotherapeutics with pH-sensitive activation. Nanomedicine Nanotechnology Biology and Medicine. 56. 102730–102730.
7.
Sytar, Oksana, et al.. (2023). Cultivar-dependent and drought-induced modulation of secondary metabolites, adaptative defense in Fagopyrum esculentum L. Physiology and Molecular Biology of Plants. 29(10). 1605–1618. 14 indexed citations
8.
Glassman, Caleb R., Leon Su, Hauke Winkelmann, et al.. (2021). Calibration of cell-intrinsic interleukin-2 response thresholds guides design of a regulatory T cell biased agonist. eLife. 10. 24 indexed citations
10.
Truxová, Iva, Lenka Kašíková, Cyril Šálek, et al.. (2019). Calreticulin exposure on malignant blasts correlates with improved natural killer cell-mediated cytotoxicity in acute myeloid leukemia patients. Haematologica. 105(7). 1868–1878. 43 indexed citations
11.
Šírová, Milada, P Roßmann, Robert Pola, et al.. (2015). The structure-dependent toxicity, pharmacokinetics and anti-tumour activity of HPMA copolymer conjugates in the treatment of solid tumours and leukaemia. Journal of Controlled Release. 223. 1–10. 35 indexed citations
12.
Kovář, Marek, et al.. (2014). SUNFLOWER (HELIANTHUS ANNUUS. L.) YIELD-FORMING ELEMENTS INFLUENCED BY YEAR WEATHER CONDITIONS AND APPLICATIONS OF BIOLOGICAL PREPARATIONS TERRA-SORB AND UNICUM. SHILAP Revista de lepidopterología. 1 indexed citations
13.
Řı́hová, Blanka, Tomáš Etrych, Milada Šírová, et al.. (2011). Synergistic effect of EMF–BEMER-type pulsed weak electromagnetic field and HPMA-bound doxorubicin on mouse EL4 T-cell lymphoma. Journal of drug targeting. 19(10). 890–899. 9 indexed citations
16.
Řı́hová, Blanka & Marek Kovář. (2009). Immunogenicity and immunomodulatory properties of HPMA-based polymers☆. Advanced Drug Delivery Reviews. 62(2). 184–191. 75 indexed citations
17.
Boyman, Onur, Marek Kovář, Mark P. Rubinstein, Charles D. Surh, & Jonathan Sprent. (2006). Selective Stimulation of T Cell Subsets with Antibody-Cytokine Immune Complexes. Science. 311(5769). 1924–1927. 719 indexed citations breakdown →
18.
Řı́hová, Blanka, J. Strohalm, Kateřina Kubáčková, et al.. (2005). Drug-HPMA-HuIg Conjugates Effective Against Human Solid Cancer. Kluwer Academic Publishers eBooks. 519. 125–143. 18 indexed citations
19.
Kovář, Marek, Lubomír Kovář, Vladimír Šubr, et al.. (2004). HPMA copolymers containing doxorubicin bound by a proteolytically or hydrolytically cleavable bond: comparison of biological properties in vitro. Journal of Controlled Release. 99(2). 301–314. 38 indexed citations
20.
Kovář, Marek, Tomáš Mrkvan, J. Strohalm, et al.. (2003). HPMA copolymer-bound doxorubicin targeted to tumor-specific antigen of BCL1 mouse B cell leukemia. Journal of Controlled Release. 92(3). 315–330. 44 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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